code: def download_tcia_series_instance(
      series_uid: str,
      download_dir: PathLike,
      output_dir: PathLike,
      check_md5: bool = False,
      hashes_filename: str = "md5hashes.csv",
      progress: bool = True,
  ) -> None:
      """
      Download a dicom series from a public The Cancer Imaging Archive (TCIA) dataset.
      The downloaded compressed file will be stored in `download_dir`, and the uncompressed folder will be saved
      in `output_dir`.
  
      Args:
          series_uid: SeriesInstanceUID of a dicom series.
          download_dir: the path to store the downloaded compressed file. The full path of the file is:
              `os.path.join(download_dir, f"{series_uid}.zip")`.
          output_dir: target directory to save extracted dicom series.
          check_md5: whether to download the MD5 hash values as well. If True, will check hash values for all images in
              the downloaded dicom series.
          hashes_filename: file that contains hashes.
          progress: whether to display progress bar.
  
      """
      query_name = "getImageWithMD5Hash" if check_md5 else "getImage"
      download_url = (
          f"{BASE_URL}{query_name}?SeriesInstanceUID={series_uid}"
      )
  
      monai.apps.utils.download_and_extract(
          url=download_url,
          filepath=os.path.join(download_dir, f"{series_uid}.zip"),
          output_dir=output_dir,
          progress=progress,
      )
      if check_md5:
          if not has_pandas:
              raise ValueError(
                  "pandas package is necessary, please install it."
              )
          hashes_df = pd.read_csv(
              os.path.join(output_dir, hashes_filename)
          )
          for dcm, md5hash in hashes_df.values:
              monai.apps.utils.check_hash(
                  filepath=os.path.join(output_dir, dcm),
                  val=md5hash,
                  hash_type="md5",
              )
  
file_path: MONAI/monai/apps/tcia/utils.py
imports: from __future__ import annotations
  import os
  from typing import Iterable
  import monai
  from monai.config.type_definitions import PathLike
  from monai.utils import optional_import
label_desc: Use image node_id 2 for calling a global function with example usage: download_tcia_series_instance(series_uid, download_dir, output_dir, check_md5, hashes_filename, progress) without return types